In the course of reviewing hundreds of articles, blogs, white papers, and videos about AI, I found volumes of information about its potential benefits, promising products, mind-numbing technologies… and endless amounts of hype. But surprisingly, I couldn’t find an in-depth, cold-eyed examination of AI in a business context and its potential effects on businesses.

Paradigm shifts are hard, and often full of surprises. The tectonic shift that AI imposes only magnifies these challenges. As business leaders, are we prepared to face them? Are we equipped with the knowledge and forethought to wager our business’ money, time, people, organizational stability, and energy on AI?

Before answering this question, consider a few others:

– What exactly is AI? Is it technology, a solution, a product, a process, a category? Is there a way to deconstruct the thing we know as AI in a way that makes sense to non-technical business leaders?

– Why has AI seemingly burst on the scene? If it’s so powerful, why has it become prevalent only recently?

– Is my organization ready for AI? Have we identified the problems and use cases that would help us focus on bringing the most value to our business?

– Do we have the right data? Do we have the knowledge and expertise to design and implement AI solutions? Can we sustain them?  Can we defend their results?

– If we aren’t ready for AI, are we at a disadvantage when compared to our peers who are already leveraging it? How can we gauge our maturity with AI and identify gaps where we must improve?

– Is AI the best approach for addressing a specific business problem? Are there non-AI alternatives? What are the pros and cons of each? Do we have the expertise to make these determinations?

– Is an AI approach even viable? Isn’t this the fundamental question when considering an AI initiative? Is there a way to determine this early in a project before making a significant investment?

– How can we establish a measurable ROI and identify the value we intend to gain from an AI project?

– In the past, has my organization been susceptible to “shiny object syndrome” – the inability to resist the temptation of software marketing hype. How do we know enough to resist its allure?

– The premise and promise of AI means that some people’s jobs are going to change. Organization structures frequently need to change at the same time. Change is hard. Are we equipped to anticipate, understand, prepare for, and act on it successfully?

– AI frequently introduces new, unfamiliar ethical questions. Recognizing this reality, do we have the experience and expertise to identify and address these issues up front?

– The probabilistic nature of AI means that the governance structures that we are familiar with must change to be effective. Are we equipped to curate and govern interrelated data, models, and result sets in a way that support repeatability and explainability? What about audits?

– Finally, how can we determine if we’ve achieved the return and value that we set out to gain from an AI project? How do we declare victory? And is there a way to further leverage the outcome to uncover additional value?

These questions, and more, will shape this blog series.  Along the way, we’ll explore a wide range of AI-related topics that directly and indirectly impact business, and we’ll provide some suggestions, or at least food for thought. While I and my fellow co-authors have something to offer business leaders, we certainly don’t claim to know everything about AI or its uses in the business realm. We look forward to your comments and suggestions – please don’t be shy. Let’s figure out how to make AI happen together.

In parting, consider this observation by the late, great Vince Lombardi: